Passive Measurement Method of Tree Height and Crown Diameter Using a Smartphone

The tree height and crown diameter are important measurement attributes in forest resource survey and management. Hence, we propose a passive measurement method of tree height and crown diameter based on monocular camera of a smartphone. First, we use an feature-adaptive Mean-Shift algorithm to segm...

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Main Authors: Wu Xinmei, Xu Aijun, Yang Tingting
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/8957490/
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spelling doaj-28da902a0ed04a14a11c582cfb9cc4722021-03-30T03:06:22ZengIEEEIEEE Access2169-35362020-01-018116691167810.1109/ACCESS.2020.29652168957490Passive Measurement Method of Tree Height and Crown Diameter Using a SmartphoneWu Xinmei0https://orcid.org/0000-0001-7983-454XXu Aijun1https://orcid.org/0000-0001-6789-6938Yang Tingting2https://orcid.org/0000-0001-5441-1188School of Information Engineering, Zhejiang Agriculture Forestry University, Hangzhou, ChinaSchool of Information Engineering, Zhejiang Agriculture Forestry University, Hangzhou, ChinaSchool of Information Engineering, Zhejiang Agriculture Forestry University, Hangzhou, ChinaThe tree height and crown diameter are important measurement attributes in forest resource survey and management. Hence, we propose a passive measurement method of tree height and crown diameter based on monocular camera of a smartphone. First, we use an feature-adaptive Mean-Shift algorithm to segment the image and extract tree's contour. Furthermore, an adaptive feature coordinate system is established to help study the conversion relationship of the coordinate systems. It has been proved that for the image points with the same abscissa pixels, their ordinate pixels have a linear relationship with its actual imaging angles. A depth extraction model is built according to this principle. Then, we obtain the rotation and translation matrix and established tree height and crown diameter models according to the mapping transformation relationship of coordinates. Experimental results reveal significant correlation between calculated and truth values. The RMSE is 0.267 m (rRMS=2.482%) for tree height and 0.209 m (rRMS=5.631%) for crown diameter. The relative errors of tree heights are less than 5.76% (MRE=2.159%); for crown diameter, the relative errors are less than 9.73% (MRE=4.95%). Overall, the accuracy of this method falls within the requirements of the continuous inventory of Chinese national forest resources.https://ieeexplore.ieee.org/document/8957490/Tree heightcrown diametermonocular visionpassive Measurementdepth extraction model
collection DOAJ
language English
format Article
sources DOAJ
author Wu Xinmei
Xu Aijun
Yang Tingting
spellingShingle Wu Xinmei
Xu Aijun
Yang Tingting
Passive Measurement Method of Tree Height and Crown Diameter Using a Smartphone
IEEE Access
Tree height
crown diameter
monocular vision
passive Measurement
depth extraction model
author_facet Wu Xinmei
Xu Aijun
Yang Tingting
author_sort Wu Xinmei
title Passive Measurement Method of Tree Height and Crown Diameter Using a Smartphone
title_short Passive Measurement Method of Tree Height and Crown Diameter Using a Smartphone
title_full Passive Measurement Method of Tree Height and Crown Diameter Using a Smartphone
title_fullStr Passive Measurement Method of Tree Height and Crown Diameter Using a Smartphone
title_full_unstemmed Passive Measurement Method of Tree Height and Crown Diameter Using a Smartphone
title_sort passive measurement method of tree height and crown diameter using a smartphone
publisher IEEE
series IEEE Access
issn 2169-3536
publishDate 2020-01-01
description The tree height and crown diameter are important measurement attributes in forest resource survey and management. Hence, we propose a passive measurement method of tree height and crown diameter based on monocular camera of a smartphone. First, we use an feature-adaptive Mean-Shift algorithm to segment the image and extract tree's contour. Furthermore, an adaptive feature coordinate system is established to help study the conversion relationship of the coordinate systems. It has been proved that for the image points with the same abscissa pixels, their ordinate pixels have a linear relationship with its actual imaging angles. A depth extraction model is built according to this principle. Then, we obtain the rotation and translation matrix and established tree height and crown diameter models according to the mapping transformation relationship of coordinates. Experimental results reveal significant correlation between calculated and truth values. The RMSE is 0.267 m (rRMS=2.482%) for tree height and 0.209 m (rRMS=5.631%) for crown diameter. The relative errors of tree heights are less than 5.76% (MRE=2.159%); for crown diameter, the relative errors are less than 9.73% (MRE=4.95%). Overall, the accuracy of this method falls within the requirements of the continuous inventory of Chinese national forest resources.
topic Tree height
crown diameter
monocular vision
passive Measurement
depth extraction model
url https://ieeexplore.ieee.org/document/8957490/
work_keys_str_mv AT wuxinmei passivemeasurementmethodoftreeheightandcrowndiameterusingasmartphone
AT xuaijun passivemeasurementmethodoftreeheightandcrowndiameterusingasmartphone
AT yangtingting passivemeasurementmethodoftreeheightandcrowndiameterusingasmartphone
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